Experimental validation of methods for differential gene expression analysis and sample pooling in RNA-seq

TY - JOUR

T1 - Experimental validation of methods for differential gene expression analysis and sample pooling in RNA-seq

AU - Rajkumar, Anto

AU - Qvist, Per

AU - Lazarus, Ross

AU - Lescai, Francesco

AU - Ju, Jia

AU - Nyegaard, Mette

AU - Mors, Ole

AU - Børglum, Anders D

AU - Li, Qibin

AU - Christensen, Jane H

PY - 2015

Y1 - 2015

N2 - Background Massively parallel cDNA sequencing (RNA-seq) experiments are gradually superseding microarrays in quantitative gene expression profiling. However, many biologists are uncertain about the choice of differentially expressed gene (DEG) analysis methods and the validity of cost-saving sample pooling strategies for their RNA-seq experiments. Hence, we performed experimental validation of DEGs identified by Cuffdiff2, edgeR, DESeq2 and Two-stage Poisson Model (TSPM) in a RNA-seq experiment involving mice amygdalae micro-punches, using high-throughput qPCR on independent biological replicate samples. Moreover, we sequenced RNA-pools and compared their results with sequencing corresponding individual RNA samples. Results False-positivity rate of Cuffdiff2 and false-negativity rates of DESeq2 and TSPM were high. Among the four investigated DEG analysis methods, sensitivity and specificity of edgeR was relatively high. We documented the pooling bias and that the DEGs identified in pooled samples suffered low positive predictive values. Conclusions Our results highlighted the need for combined use of more sensitive DEG analysis methods and high-throughput validation of identified DEGs in future RNA-seq experiments. They indicated limited utility of sample pooling strategies for RNA-seq in similar setups and supported increasing the number of biological replicate samples.

AB - Background Massively parallel cDNA sequencing (RNA-seq) experiments are gradually superseding microarrays in quantitative gene expression profiling. However, many biologists are uncertain about the choice of differentially expressed gene (DEG) analysis methods and the validity of cost-saving sample pooling strategies for their RNA-seq experiments. Hence, we performed experimental validation of DEGs identified by Cuffdiff2, edgeR, DESeq2 and Two-stage Poisson Model (TSPM) in a RNA-seq experiment involving mice amygdalae micro-punches, using high-throughput qPCR on independent biological replicate samples. Moreover, we sequenced RNA-pools and compared their results with sequencing corresponding individual RNA samples. Results False-positivity rate of Cuffdiff2 and false-negativity rates of DESeq2 and TSPM were high. Among the four investigated DEG analysis methods, sensitivity and specificity of edgeR was relatively high. We documented the pooling bias and that the DEGs identified in pooled samples suffered low positive predictive values. Conclusions Our results highlighted the need for combined use of more sensitive DEG analysis methods and high-throughput validation of identified DEGs in future RNA-seq experiments. They indicated limited utility of sample pooling strategies for RNA-seq in similar setups and supported increasing the number of biological replicate samples.

KW - Animals

KW - DNA, Complementary

KW - High-Throughput Nucleotide Sequencing

KW - Mice

KW - Sequence Analysis, RNA

KW - Software

U2 - 10.1186/s12864-015-1767-y

DO - 10.1186/s12864-015-1767-y

M3 - Article

C2 - 26208977

SN - 1471-2164

VL - 16

SP - 1

EP - 8

JO - BMC GENOMICS

JF - BMC GENOMICS

M1 - 548

ER -